Abstract
It is becoming increasingly apparent that wide application of electric vehicles (EVs) are subject to significant improvements in battery technology. Temperature sensitivity is a major issue adversely affecting battery performance and requiring a robust thermal control. Yet, this is challenged by the large variety of temporal scenarios though which heat is generated in a battery pack, demanding dynamic tools to predict the thermal evolution of batteries. Classical transfer functions provide a low-cost and effective predictive tool. However, they are limited to linear systems, while nonlinear predictive tools can become impractical for EV applications. Therefore, this study provides a methodology to assess the dynamics of battery cooling. This is achieved through conduction of high fidelity modelling of battery cooling exposed to different temporal disturbances on the internal heat generation. The results are then post-processed to evaluate the extent of linearity. A quantitative measure of non-linearity is further applied to clearly determine the degree of nonlinearity in the heat transfer response. It is shown that battery cooling system can be approximated as a linear dynamical system as long as the disturbances are of short duration and relatively low amplitude. Conversely, long and large amplitude temporal disturbances can render strongly nonlinear thermal responses.
Highlights
Electric Vehicles (EV) and Hybrid Electric Vehicles (HEV) have recently gained enormous attention due to rising environmental concerns [1]
The performance e life cycle, discharge capacity e and safety of these batteries are heavily affected by the operational temperature [7e10]
The use of a passive thermal management system combined with forced air convection provided an efficient means to minimise cell to cell temperature difference while the battery pack was kept at an acceptable temperature range
Summary
Electric Vehicles (EV) and Hybrid Electric Vehicles (HEV) have recently gained enormous attention due to rising environmental concerns [1]. Using StarCCM þ for simulating and analysing the heat transfer and fluid dynamics of the cooling system, the study indicated that the cell's temperatures and temperature differences could be kept within an ideal range. Ling et al [20] further studied the effects of varying air speed and the thermophysical properties of the PCMs. The use of a passive thermal management system combined with forced air convection provided an efficient means to minimise cell to cell temperature difference while the battery pack was kept at an acceptable temperature range. The preceding review of literature indicated that the existing BTMSs are primarily concerned with accurately evaluating the temperature field of the cooling fluid and heat generation inside battery cells This requires the use of very demanding computations to precisely predict the thermal behaviour of battery cells.
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